湖南中医药大学学报2024，Vol.44Issue(7)：1254-1260,7.DOI:10.3969/j.issn.1674-070X.2024.07.016
基于卷积神经网络的"舌边白涎"舌象识别研究
Tongue image recognition of "white saliva on the tongue side" based on convolutional neural network
摘要
Abstract
Objective To study the local feature recognition of tongue image through machine-learning analysis on the characteristics of"white saliva on the tongue side",and to explore the performance of convolutional neural network algorithms in identifying tongue images application.Methods Python was used for image preprocessing,and visual geometry group 16(VGG16)convolutional neural network model was built for tongue image recognition.The effect of the model on tongue image recognition of"white saliva on the tongue side"was identified and analyzed,and the typical tongue image performance of"white saliva on the tongue side"was analyzed combined with heat map.Results Based on PyTorch framework,tongue image identification research of convolutional neural network was carried out.The verification accuracy of VGG16 and residual network 50(ResNet50)models were high,reaching over 80%,and the ResNet50 model outperformed the VGG16 model,providing a certain reference for tongue image recognition.Based on gradient-weighted class activation mapping(Grad-CAM)technology,the network visualization of the difference distribution of tongue coating and tongue color was helpful for intuitive model evaluation and analysis.Conclusion The analysis of tongue image database based on convolutional neural network model can realize the tongue image recognition of"white saliva on the tongue side",which is helpful for objectified auxiliary analysis in clinical diagnosis and treatment,and provides some references for the intelligent development of tongue diagnosis.关键词
卷积神经网络/视觉几何组/Python/人工智能/舌边白涎Key words
convolutional neural network/visual geometry group/Python/artificial intelligence/white saliva on the tongue side分类
医药卫生引用本文复制引用
李秋华,史国峰,李玥博,任路..基于卷积神经网络的"舌边白涎"舌象识别研究[J].湖南中医药大学学报,2024,44(7):1254-1260,7.基金项目
中国博士后科学基金项目(2021MD703842) （2021MD703842）
国家中医药管理局中医药国际合作专项项目(0610-2140NF020629) （0610-2140NF020629）
辽宁省自然科学基金计划重点项目(20180540043). （20180540043）
